Using systematic data categorisation to quantify the types of data collected in clinical trials: the DataCat project.
Evelyn CrowleyShaun TreweekKatie BanisterSuzanne BreemanLynda ConstableSeonaidh CottonAnne DuncanAdel El FekyHeidi GardnerKirsteen GoodmanDoris LanzAlison McDonaldEmma OgburnKath StarrNatasha StevensMarie ValenteGordon FerniePublished in: Trials (2020)
A small proportion of the data collected in our sample of 18 trials was related to the primary outcome. Secondary outcomes accounted for eight times the volume of data as the primary outcome. A substantial amount of data collection is not related to trial outcomes. Trialists should work to make sure that the data they collect are only those essential to support the health and treatment decisions of those whom the trial is designed to inform.
Keyphrases
- electronic health record
- clinical trial
- big data
- healthcare
- public health
- study protocol
- randomized controlled trial
- data analysis
- phase ii
- metabolic syndrome
- risk assessment
- machine learning
- mental health
- quality improvement
- adipose tissue
- deep learning
- weight loss
- artificial intelligence
- health information
- glycemic control
- double blind
- drug induced